Search results

The purpose of this paper is to suggest a bibliometric method for designing agent-based models (ABMs) in entrepreneurship research. The application of this method is illustrated with an exemplary agent-based modeling and simulation (ABMS) regarding the early venture growth process. This bibliometric approach invigorates the utilization of ABMS as a viable research methodology in process-oriented entrepreneurship research.

In the bibliometric method, a domain corpus composed of scholarly articles is established and systematically analyzed through co-word analysis to discern essential concepts (i.e. agents, objects, and contexts) and their interrelations. The usefulness of the bibliometric method is elucidated by constructing an illustrative ABMS.

The bibliometric method for designing ABMs identifies essential concepts in the entrepreneurship literature and provides contexts in which the concepts are interrelated. The illustrative ABMS based on these concepts and interrelations accurately and consistently reproduces the emergence of power-law distributions in venture outcomes consistent with empirical evidence, implying further merit to bibliometric procedures.

The proposed method can be used not only to build simple models with essential concepts, but also to build more complex models that take a large number of concepts and their interrelations into consideration.

This study proposes a bibliometric method for designing ABMs. The proposed method extends similar procedures that are limited to thematic or cluster analysis by examining the semantic contexts in which the concepts co-occur. This research suggests that ABMS from bibliographic sources can be built and validated with empirical evidence. Several considerations are provided for the combined utilization of the bibliometric method and ABMS in entrepreneurship.

This study aims to offer a comprehensive exploration of the potential and challenges associated with sensor fusion-based virtual reality (VR) applications in the context of enhanced physical training. The main objective is to identify key advancements in sensor fusion technology, evaluate its application in VR systems and understand its impact on physical training.

The research initiates by providing context to the physical training environment in today’s technology-driven world, followed by an in-depth overview of VR. This overview includes a concise discussion on the advancements in sensor fusion technology and its application in VR systems for physical training. A systematic review of literature then follows, examining VR’s application in various facets of physical training: from exercise, skill development and technique enhancement to injury prevention, rehabilitation and psychological preparation.

Sensor fusion-based VR presents tangible advantages in the sphere of physical training, offering immersive experiences that could redefine traditional training methodologies. While the advantages are evident in domains such as exercise optimization, skill acquisition and mental preparation, challenges persist. The current research suggests there is a need for further studies to address these limitations to fully harness VR’s potential in physical training.

The integration of sensor fusion technology with VR in the domain of physical training remains a rapidly evolving field. Highlighting the advancements and challenges, this review makes a significant contribution by addressing gaps in knowledge and offering directions for future research.